在UML设计模型中生成和评估修复不一致性的选择

Alexander Egyed, Emmanuel Letier, A. Finkelstein
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引用次数: 144

摘要

我们的目标是为帮助设计人员修复UML模型中的不一致性提供自动化支持。我们以前已经开发了一些技术,用于有效地检测这些模型中的不一致性,并确定需要进行更改的位置,以便修复通过这些方法检测到的问题。本文通过描述一种技术来扩展以前的工作,该技术可以自动生成一组具体的更改,用于修复不一致性,并提供关于每个更改对所有一致性规则的影响的信息。该方法与设计工具IBM Rational Rose集成在一起。我们通过对39个UML模型的规模高达120,000个元素的经验评估来演示该方法的计算可伸缩性和可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generating and Evaluating Choices for Fixing Inconsistencies in UML Design Models
Our objective is to provide automated support for assisting designers in fixing inconsistencies in UML models. We have previously developed techniques for efficiently detecting inconsistencies in such models and identifying where changes need to occur in order to fix problems detected by these means. This paper extends previous work by describing a technique for automatically generating a set of concrete changes for fixing inconsistencies and providing information about the impact of each change on all consistency rules. The approach is integrated with the design tool IBM Rational Rose . We demonstrate the computational scalability and usability of the approach through the empirical evaluation of 39 UML models of sizes up to 120,000 elements.
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